To succeed, the smartest people study failure

It’s often said that the most successful entrepreneurs are the ones who have failed at least once in business before going on to create successful enterprises.

And it isn’t difficult to find business gurus advising entrepreneurs and innovators with phrases like “embrace failure” and “fail fast, fail often”.

The reality is that most entrepreneurs, as well as small and medium-sized companies, cannot afford to fail – not even once, let alone “often”.

The simple reason is that they have limited resources. A single expensive failure may destroy everything they have worked for. And the often-advised “bounce back” from failure can in reality be a long grind over many years.

If you are a big company or multinational with abundant resources you also cannot afford to “fail fast, fail often”. Sooner or later – usually sooner – shareholders and senior execs eager for big, fast success will lose patience and your career may take a direction that you just don’t want.

In the food and beverage industry, failure is much easier to achieve than success. For a whole variety of reasons, about 80%+ of new products fail.

So to help all those people who prefer success to failure, we’ve taken the advice of the great Warren Buffett, the world’s 3rd-richest man. Mr. Buffett doesn’t use empty phrases like “embrace failure”. He says: “I like to study failure”. By studying the failures of others, he believes, you can learn what not to do – as well as what you need to do to succeed.

Our motivation in writing our new report, Failures in Functional Foods & Beverages was to take everything we have learned in 17 years of qualitatively and quantitatively studying failures and condense it into a simple form that anyone can use to understand the 12 most common mistakes – and how to avoid them.

We support our explanation with 22 Case Studies from the US, Europe and Brazil. They span dairy, beverages and snacking and range from failures by giants like Nestle down to local brands.

Thanks to some painstaking research, we’ve even been able to build a statistical model that we’re confident can predict whether a new product will succeed or fail, and why.